Evolution of triclosan resistance modulates bacterial permissiveness to multidrug resistance plasmids and phages

The horizontal transfer of plasmids has been recognized as one of the key drivers for the worldwide spread of antimicrobial resistance (AMR) across bacterial pathogens. However, knowledge remain limited about the contribution made by environmental stress on the evolution of bacterial AMR by modulating horizontal acquisition of AMR plasmids and other mobile genetic elements. Here we combined experimental evolution, whole genome sequencing, reverse genetic engineering, and transcriptomics to examine if the evolution of chromosomal AMR to triclosan (TCS) disinfectant has correlated effects on modulating bacterial pathogen (Klebsiella pneumoniae) permissiveness to AMR plasmids and phage susceptibility. Herein, we show that TCS exposure increases the evolvability of K. pneumoniae to evolve TCS-resistant mutants (TRMs) by acquiring mutations and altered expression of several genes previously associated with TCS and antibiotic resistance. Notably, nsrR deletion increases conjugation permissiveness of K. pneumoniae to four AMR plasmids, and enhances susceptibility to various Klebsiella-specific phages through the downregulation of several bacterial defense systems and changes in membrane potential with altered reactive oxygen species response. Our findings suggest that unrestricted use of TCS disinfectant imposes a dual impact on bacterial antibiotic resistance by augmenting both chromosomally and horizontally acquired AMR mechanisms.

1.The methods are not presented in the order in which they are used in the results.2. Fig 1 a bottom > this is final OD600nm, i.e. measured just before the transfer.This needs to be clear in the figure legend and caption.3. Fig 1b : choose shorter and more explicit names for the clones characterized.It is important that the reader can identify and compare rapidly the ancestor, clones from day 7 and clones from day 10. 4. L123-126: the reference is to supplementary table 5 and not 4 (or more precisely, Table S4 and S5 should be in reversed order).From current table S5, it is clear that evolution in increasing concentrations of TCS has led to increased resistance to ciprofloxacin, cefotaxime and Fosfomycin but not to the other antibiotics tested and this should be also reported in the results.5. Fig 2b : gene names seem to be written in to different polices + it would be useful to highlight genes involved in Ab resistance (those represented in fig 2c).6. L178 should read "In addition to the changes in the expression of genes involved in ABR, …".If I understand correctly the down regulation of defense mechanisms is also a result from the transcriptomic analysis and figure 3a is a sub-part of figure 2b with different genes annotated.7. L199-200 should read "For donors, we used four E. coli MG1655 carrying each one of four different AMR plasmids" 8. L204: "and" should be removed.9. L209-214: redundancies 10.L233: figS2 does not show this.11.L244: figS4 and not S3 should be referenced here.12. L233-244: again nsrR KO are not a good proxy for the effect of mutations obtained in experimental evolution.13.L262: "least" should be changed to "the least" or "less".14.L266-268: this sentence is grammatically incorrect 15.L342: remove one "be" 16.L424: verb missing 17.L446: "sequenced" should be "sequencing" 18. L874: "one replicate" should be "replicate 1".19.L911-912: what does "flow plots two independent replicates were performed" mean?
Reviewer #2 (Remarks to the Author): I am happy to inform you that after evaluation, the authors have satisfactorily addressed all of my concerns, resulting in a significant improvement in the quality of this almost-new submission.As a result, I no longer have any objections to the manuscript's publication.
Reviewer #3 (Remarks to the Author): While the authors have conducted additional analysis to address reviewers' comments, they failed to address the most critical limitation raised for the original submission (also noted by other reviewers).
The potentially most interesting aspect of the work is the increased HGT in the evolved clones.However, the quantification of this trait is not convincing due to the prolonged culturing (16hrs) before measuring transconjugants.The issue is not only whether this was done using plating or flow, but the very nature of prolonged culturing.The authors provided more measurements on additional clones but none of these addressed the critical technical limitation.On that note, the flow measurements are not clearly described with regard to how it's calibrated.The corresponding figure panels are missing labels.Therefore, I am not confident in this conclusion.And I think the significance of the work rests upon the demonstration of this point.
Additionally, they used a competition assay to measure the plasmid fitness, which is not suitable in this case as the plasmids are transferable.The relative abundances after the "competition" confound both growth competition and potential gene transfer during this time window.
There are also other issues with the manuscript both in clarity of presentation and rigor of analysis.The text remains to be difficult to read.The reporting of statistical analysis is also quite sloppy.For example, at least in one case, they reported an exceedingly small p value of 5.76x10^-108, which is a recognized poor practice.

REVIEWER COMMENTS
Reviewer #1 (Remarks to the Author): I had previously reviewed the manuscript by Yang and collaborators when it had been submitted to [Redacted].This new version represents a clear improvement and the authors have performed additional experiments, redone analyses and deeply rewritten the manuscript.However, the general impression of lack of rigour is still present, although to a lesser extent than before.I list below the points that need to be addressed.
Response: we thank reviewer#1 for very useful comments.In accordance with all reviewers' suggestions, we have thoroughly revised the manuscript to fully address all reviewers' comments.To add more rigor to our findings, we have made the required modifications in the main text, and extensively revised the key figures (Fig. 1-Fig.4).We also provide more robust evidence for the increased plasmid permissiveness of triclosan resistant mutants, by measuring the plasmid transfer at different time points cross 24 hours using flow cytometry and confocal microscopy.In the revised manuscript, changes in the main text were all tracked and the detailed point-by-point rebuttal are listed below.
1.The novelty of the paper mainly resides in the increased conjugation rates and phage sensibility of the populations evolved in presence of triclosan and the exploration of a potential mechanistic explanation for this pleiotropic effect.The part on TCS resistance evolution and evolution of cross-resistance to other antibiotics could be shortened to get more rapidly to the most interesting and newest point.This finding should also be discussed in the context of other recent studies on similar questions (e.g.Xuan et al. 2022Xuan et al. doi: 10.1128/spectrum.01356-22;/spectrum.01356-22;Chen et al. https://www.nature.com/articles/s41598-017-06688-w;Chan et al.https://www.nature.com/articles/srep26717).
Response: we have tried earnestly to reduce the text in accordance with reviewer's comments without compromising the rigor of data and analysis.as suggested, the results of TCS resistance evolution and mutations have been substantially shortened (L130-177).We have also re-arranged the figures (Fig. 1-4) and showed the increased conjugation rates in Fig. 2-3, and phage sensibility showed in separate figures (Fig. 4 and supplementary Fig. S6-8) The two suggested references have been discussed in the Discussion (L373-374).
2. Whole genome sequencing: there is still a lot of confusion about the number and the identity of the clones sequenced.The results section says "five clones from day 7" and then mentions "other clones from day 8 and 10. Figure 2 legend says "five from day 7 + two from day 10".Methods says "13 TRMs from day 7 to 10" which corresponds to the content of table S4.Even more importantly, it is still not clear to me whether clones from different days are sampled from independent experimentally evolved populations.The interpretation of finding the same mutations in clones from different time points, although informative in both cases, is quite different depending on whether they come from the same population or not.
Response: we apologize for the confusion in how we describe the selection of evolved clones.Here, we would like to provide a gantt chart to clarify the number and the identity of the evolved clones sequenced.As described in method (L442) and the below table, in total we sequenced 13 evolved clones isolated across different time points (Table S4).
To avoid any overstatement of gene mutations in the evolved clones (in light of previous reviewers' comments), we chose five evolved clones from independent replicates at day7 and two final evolved clones from day10 for our conjugation and phage susceptibility experiments (Fig. 2-4, L147-149).
We hope we have provided a clearer explanation for how the number and identity of the evolved clones were chosen.
3. L225-226: where does this affirmation come from?Please refer to a figure, a table, a statistical test + "singularly responsible" should "responsible alone" + as mentioned in my first review, the mutations in nsrR in exp evol populations are non-synonymous SNPs so there was no reason to expect that KO would recapitulate the effect of these mutations.
Although we failed to generate the point mutation on nsrR after numerous attempts, our results strongly suggest that nsrR can modulate the conjugation permissiveness to AMR plasmids and phage sensibility.As queried by reviewer#3, in this revised manuscript, we have repeated one conjugation experiment with pFII_mcr-8 plasmid, to measure the conjugation rates at different time points (revised Fig. 3).The evolved d10-2 and nsrR  knockout strain showed significantly increased conjugation rates after 8 hours coincubation (Fig. 3 and supplementary Fig. S5).
Furthermore, in the accordance with reviewers' comments, we have addressed this issue as a limitation in the Discussion (L388-390).4. L114-115 "re-exposed to 2 and 4mg/L of TCS in short-term growth assays."+ FigS1: I do not understand the interest of getting this growth curves as the clones have been isolated at days where the TCS concentration was equal or superior to 4mg/L, so it is clear that they are able to grow at these two concentrations.The only piece of info from figure S1 is that TCS resistance has a cost in absence of TCS (TRMs grow less than the ancestor at 0mg/L), but this is not mentioned neither in the results nor in the discussion.More specifically, on l114-115, no results are actually given for this specific assay and as the following sentence is about MIC, it seems that the MIC have been obtained by this "short-term growth assay" but this is technically not possible (broader concentration range needed), so it is inducing confusion.
Response: this sentence has been rewritten (L113-116), the MIC of triclosan was determined by agar dilution protocol, which has also mentioned in the method section (L421-431).We have replaced the supplementary Fig. S1 with the growth curves of nsrR and ndh knockout strains.
Minor points These points are minor but all together they contribute to the impression of lack of rigour.1.The methods are not presented in the order in which they are used in the results.Response: we have added methodological details for conjugation experiment measuring by flow cytometry and microscopy (L574-585), as well as re-arranged the methods section, to chronologically present the methodological approach.
2. Fig 1 a bottom > this is final OD600nm, i.e. measured just before the transfer.This needs to be clear in the figure legend and caption.Response: final OD600nm has been revised throughout the manuscript.In the Methods, we have clarified that bacterial density was measured before each transfer (L426-428).

Fig 1b:
choose shorter and more explicit names for the clones characterized.It is important that the reader can identify and compare rapidly the ancestor, clones from day 7 and clones from day 10.Response: the names of evolved strains have been shortened by removal of strain ID (Kp85-).the naming code is based on time-points and replicates.For example, d10-2 name indicates that the evolved clone was isolated from day 10 in replicate 2). 4. L123-126: the reference is to supplementary table 5 and not 4 (or more precisely, Table S4 and S5 should be in reversed order).From current table S5, it is clear that evolution in increasing concentrations of TCS has led to increased resistance to ciprofloxacin, cefotaxime and Fosfomycin but not to the other antibiotics tested and this should be also reported in the results.
Response: The order of Table S4 and S5  Response: As there were over 400 genes differentially expressed in evolved d10-2 strain, it is difficult to highlight the Ab resistance genes in Fig. S2c (moved to the supplementary Figure ), this is also the reason for providing the Fig. S4 (moved to the supplementary Figure ), specifically listing the Ab and TCS resistance genes.

Reviewer #2 (Remarks to the Author):
I am happy to inform you that after evaluation, the authors have satisfactorily addressed all of my concerns, resulting in a significant improvement in the quality of this almostnew submission.As a result, I no longer have any objections to the manuscript's publication.
Response: Thank you for these very positive comments.we are delighted with the positive response and the reviewer's appreciation of the significance and potential impact of this article.

Reviewer #3 (Remarks to the Author):
While the authors have conducted additional analysis to address reviewers' comments, they failed to address the most critical limitation raised for the original submission (also noted by other reviewers).
Response: we thank reviewer#3 for very useful comments.In accordance with all reviewers' suggestions, we have thoroughly revised the manuscript to fully address all reviewers' comments.To add more rigor to our findings, we have made the required modifications in the main text, and four main figures (Fig. 1-Fig.4) have been extensively revised.We also provide more robust evidence for the increased plasmid permissiveness of triclosan resistant mutants, by measuring the plasmid transfer in different time points across 24 hours using flow cytometry and confocal microscopy.In the revised manuscript, changes in the main text were all tracked and the detailed point-by-point response are listed below.
The potentially most interesting aspect of the work is the increased HGT in the evolved clones.However, the quantification of this trait is not convincing due to the prolonged culturing (16hrs) before measuring transconjugants.The issue is not only whether this was done using plating or flow, but the very nature of prolonged culturing.The authors provided more measurements on additional clones but none of these addressed the critical technical limitation.On that note, the flow measurements are not clearly described with regard to how it's calibrated.The corresponding figure panels are missing labels.Therefore, I am not confident in this conclusion.And I think the significance of the work rests upon the demonstration of this point.
Response: To add more robust evidence to our findings, we have performed time-course conjugation experiment where microscopy images/flow plots of the conjugation population were acquired at different time points (0,2,4,6,8,12,16 and 24 hours, see the Method L574-585).It is noted that no plasmid transfer occurred until 4 hours after mixing donorrecipient cells, and the number of transconjugants (green cells) was significantly increased in evolved strain d10-2 and nsrR KO strain after 8-hour mating (p<0.05),comparing to the parental Kp85anc strain (the new Fig. 3 and supplementary Fig. S5).
The method of measuring plasmid transfer by flow cytometry was inspired by previous studies that determining the RP4 plasmid transfer in bacterial populations (ref.Soren J. Sorensen et al. 2005 Nature Reviews Microbiology, Studying plasmid horizontal transfer in situ: a critical review | Nature Reviews Microbiology).In the new Fig.3a, flow plots were provided and it shows clearly that conjugation permissiveness toward pFII-mcr-8 plasmid was significantly increased in both nsrR knockout and d10-2 strain.The percentage of gfpexpressing transconjugants was also highlighted in red circle in each plot.Additionally, they used a competition assay to measure the plasmid fitness, which is not suitable in this case as the plasmids are transferable.The relative abundances after the "competition" confound both growth competition and potential gene transfer during this time window.
Response: Whilst this competition model is well defined in microbiology, we appreciate the limitation of these assays and agree with the reviewer that this method can't prevent the transfer of plasmid during the competition assay.This additional data does not affect our main findings in increasing HGT for plasmids and phage susceptibility, therefore, we have removed this analysis from the Methods and supplementary data.
There are also other issues with the manuscript both in clarity of presentation and rigor of analysis.The text remains to be difficult to read.The reporting of statistical analysis is also quite sloppy.For example, at least in one case, they reported an exceedingly small p value of 5.76x10^-108, which is a recognized poor practice.
Response: We have tried earnestly to revise the main text and figures in accordance with reviewers' comments.Four main figures have been extensively revised, especially adding more data in Figure 3 and 4.
The small p values were generated from the RNAseq data analysis, and differential gene expression analysis was conducted by the edgeR package (v3.40.2) (ref.64, Robinson et al., 2010, as showed in the Reference).This method has been well acknowledged for examining differential expression of replicated count data.The gene expression changes between the evolved clone and the parental clone were very significant, resulting in a small p-value.
The other data analysis was performed using GraphPad Prism (8.3.1).Data shown in plots are represented as mean of at least two replicates ± SEM, and exact number of independent replicates for each experiment is stated in their respective figure legends.Holm-Sidak or Wilcoxon t-test analysis (p< 0.05) was used to compare differences on conjugation experiments (see in the Methods L692-697).
I don't think the presented time courses address the central criticism I had on the paper.That is, I am not convinced by the data presented that conjugation rates have increased in the evolved strains or the knocked-out strains.They may have increased but the data are inconclusive.Specifically, as pointed out previously, the critical issue is not whether time course data are presented.Rather, it's that the experimental protocol for measuring conjugation rates is fundamentally flawed.Over the course of 24 hours (or 6-8hrs when they saw some effects), even slight differences in the growth rates of different strains can drastically affect the relative fractions of transconjugants, even if there is no change in the conjugation rate.
The nuances of various techniques to measure conjugation rates have been well recognized and discussed in detail in Huisman et al, Plasmid 2022.When growth is entwined with conjugation, it is especially difficult to provide a good estimate of conjugation rates or even to draw conclusions on whether conjugation rates have increased.While the authors conducted extensive measurements, these measurements are not well designed to determine if conjugation rates have or have not increased in various strains.
On a more minor point, I understand how the p-values are generated from the use of statistic software.However, reporting exceedingly small p-values gives a false sense of certainty and potentially masks more important control parameters, an issue that was recently discussed in Huber, Cell Syst.2019.
Reviewer #4 (Remarks to the Author): I was asked to review this paper as an arbitrating reviewer to comment on the outstanding concerns of Reviewer #1 and Reviewer #3.Regarding Reviewer #3 concerns, I agree that it would be better to present conjugation rates instead of conjugation frequencies.Conjugation rates correct for the potential biases introduced by the difference in growth rates of donors, recipients and transconjugants.There are different methods to calculate conjugation rates, such as the end point method described by Simonsen et al. (DOI: 10.1099/00221287-136-11-2319) or other more modern methods described in Huisman et al. (DOI: 10.1016/j.plasmid.2022.102627).Moreover, I'm afraid I also tend to agree with Reviewer #1 about his/her concerns leading to a "general impression of lack of rigour".

Point-to-point answers to all comments:
Reviewers' comments: Reviewer #3 (Remarks to the Author): I don't think the presented time courses address the central criticism I had on the paper.That is, I am not convinced by the data presented that conjugation rates have increased in the evolved strains or the knocked-out strains.They may have increased but the data are inconclusive.
Specifically, as pointed out previously, the critical issue is not whether time course data are presented.Rather, it's that the experimental protocol for measuring conjugation rates is fundamentally flawed.Over the course of 24 hours (or 6-8hrs when they saw some effects), even slight differences in the growth rates of different strains can drastically affect the relative fractions of transconjugants, even if there is no change in the conjugation rate.
The nuances of various techniques to measure conjugation rates have been well recognized and discussed in detail in Huisman et al, Plasmid 2022.When growth is entwined with conjugation, it is especially difficult to provide a good estimate of conjugation rates or even to draw conclusions on whether conjugation rates have increased.While the authors conducted extensive measurements, these measurements are not well designed to determine if conjugation rates have or have not increased in various strains.
Response: Firstly, we would like to apologise that we did not fully understand reviewer's request on conjugation rate experiment in the previous round of revision i.e. that we need to estimate the conjugation rate using the Simonsen's end-point method.We have now conducted additional experimental work to fully and unequivocally address these points.
To address reviewer's comments, we spent several weeks repeating all the conjugation rate experiments using the suggested Simonsen's endpoint calculation method (added in the methods, L516-528).In this "end-point" method, several key parameters have been included to estimate the conjugation rates, e.g.conjugation time and the initial/final population density of measurement.Our new results are almost identical with the conjugation estimation method we originally described in our article, providing prima facie evidence for the involvement of triclosan resistance mutants (TRMs) in broad AMR plasmid permissiveness (new data Fig. 2c-d and Fig. 3b, showed in the above rebuttal text).
Moreover, we have performed new growth curves for the evolved strains and plasmids and found no significant difference between these and ancestral Kp85anc strain (new date Fig. S1), even though evolved strains had slightly reduced carrying capacity.As a result, changes in conjugation rate were an unlikely explanation for the differences observed in growth rates between the evolved TRMs and ancestral Kp85anc strains.The previous figure Fig. 2c-d for the comparison with the above new data.This data was presented in the main text of previous version (Fig. 2c-d).Here, the transfer rates were calculated using the ratio of transconjugant cells in total bacterial cells or recipient cells.
The results are highly similar with the new method presented above (new data Fig. 2c-d).(ratio between the number of tranconjugants and recipient cells).
On a more minor point, I understand how the p-values are generated from the use of statistic software.However, reporting exceedingly small p-values gives a false sense of certainty and potentially masks more important control parameters, an issue that was recently discussed in Huber, Cell Syst.2019.
Response: Whilst the edgeR method has been recognized as a powerful and efficient tool for differential expression analysis of RNA-seq data (Baldoni, Nucleic Acid Res. 2023;Robinson, Bioinformatics. 2010), we appreciate the limitation of this assay which may give a very small P values.However, in our main text, we have designed experiments to verify the results observed in RNAseq data, for instance, the MIC test to confirm the increased/decreased expression of several resistance determinants (Fig. 1e, L181-187).And the down-regulated bacterial defense system can help to explain our main findings in increasing HGT for plasmids and phage susceptibility.
Other statistical analysis (main Fig. 1-4) were performed by prism software and all P values were indicated in the figures.In addition, we have now rounded up all the small P -values and report them as P <0.001 throughout the text.
Reviewer #4 (Remarks to the Author): I was asked to review this paper as an arbitrating reviewer to comment on the outstanding concerns of Reviewer #1 and Reviewer #3.
Regarding Reviewer #3 concerns, I agree that it would be better to present Moreover, I'm afraid I also tend to agree with Reviewer #1 about his/her concerns leading to a "general impression of lack of rigour".

Response:
To address reviewer's comments, we spent several weeks repeating all the conjugation rate experiments using the suggested Simonsen's endpoint calculation method.In this "end-point" method (added in the methods, L516-528), several key parameters have been included to estimate the conjugation rates, e.g.conjugation time and the initial/final population density of measurement.Our new results are almost identical with the conjugation estimation method we originally described in our article, providing prima facie evidence for the involvement of triclosan resistance mutants (TRMs) in broad AMR plasmid permissiveness (new data Fig. 2c-d and Fig. 3b, showed in the above figures).
Moreover, we have performed new growth curves for the evolved strains and plasmids and found no significant difference between these and ancestral Kp85anc strain (Fig. S1, showed in the above rebuttal text), even though evolved strains had slightly reduced carrying capacity.As a result, changes in conjugation rate were an unlikely explanation for the differences observed in growth rates between the evolved TRMs and ancestral Kp85anc strains.
In the revised analysis, the authors used Simonsen's endpoint method to compute the transfer rate.This is one of the several methods reviewed in the Huisman paper.This analysis is in the right direction by considering the growth of the three populations.However, while I suggested the Huisman paper as summary of various issues regarding the computation of transfer rates, I did not suggest the use of Simonsen's method.For reasons explained below, Simonsen's method may not be the optimal method and the authors were using it improperly.
Simonsen's method assumes the same growth rate for all three populations (donor, recipient, and transconjugant).
It also assumes the endpoint is still during the exponential phase.
In the methods section in the revision, I don't see how the growth rates were computed and how these assumptions were justified.From Fig S1, the different strains still have somewhat different growth rates (which should be computed during the exponential phase).From these curves, it is clear that the exponential phase has ended before 4h.
I was asked here to comment specifically on concerns about the methodology relating to conjugation rates, and remaining concerns of reviewers 3 and 4.
On the specific point of which formulas to use to calculate conjugation, I do agree with the authors.They have followed reviewers' requests to use Simonsen's endpoint model or its corrections.Prolonged culturing is not a problem as even the original Simonsen's endpoint model does not assume that the endpoint is still during the exponential phase; differences in growth rate are accounted for by the extended Simonsen's model described in Huisman et al and used here.
However, I do agree with the reviewers' worry about the data being inconclusive/unclear.
First I suspect this is partly due to the manuscript having gone through many revisions and reshuffling, it would need to be read again carefully with fresh eyes for global coherence (as an example, Fig 2 title only fits 2a and maybe b but not c to e).This also affects the conjugation rates results and methods: the method section does mix experimental methods (flow cytometry, plating, microscopy) and formulas for conjugation rate in a very confusing way.From the methods, plating data seem to still be analysed with T/N, flow cytometry by T/N and microscopy by T/D.The results shown in the main manuscript are sometimes summary data, sometimes detailed cytometry plots that I believe should all go in the supplementary data.
The results also vary depending on which experimental method is used, and this is not discussed.I personally would not have asked for this many different methods, but as they give very different results, this needs at least mentioned.Figs 2d and 2e differ by around 3 orders of magnitude for the same plasmid: What could explain this, if all methods reliably evaluate donors, recipients and transconjugants?
The unit of measurement is also lacking, making it hard to evaluate these rates (or to guess which calculation has been used).
There are also a few worrying facts in the plots: Fig 3c pX3-NDM y scale has 3. 10-16 repeated twice; and some bars have 1 single replicate visible and yet an associated p-value (Fig S6 ).
A very large amount of data is now presented, but not all of them are discussed, instead transfer rates are claimed to be constantly / consistently higher, which is not always true.E.g. line 222, MCR-8 is claimed to have "constantly higher transfer rates in the evolved d10-2 clone" -this is not true at 12h as shown in Fig 3b .And at 16h from Fig 3a there are no more transconjugants either -maybe the calculated transfer rate is higher but then providing the raw data might help understand why -does the effect arise from less donors or recipients?So any effect is not as consistent as the authors imply.P-values are shown for each time point / strain, but with so many conditions tested it is not clear if the global effect (evolved clones vs ancestor, or at least d10-2 clone across timepoints) is significant, and with which method.
Finally, the raw data need to be available to the reader.What is presented now is only end estimates of the conjugation rate, but not the raw experimental data: donor, recipient and transconjugant densities (or proportions in the case of flow cytometry) need at least to be provided, plus the growth rates needed for Simonsen's method.
Overall, I believe the conjugation data are worth publishing -and do certainly not need more experiments with more methods!-but the existing data need analysed in a more streamlined way to make the possible patterns clearer.
Two added notes, even if it is further from what I was asked to comment on: i) the refs cited l254 seem to be about transformation, not conjugation.And ii) I believe that the general argument of this manuscript about evolution of permissiveness to MGEs via down regulation of defence systems could be also supported by insisting more on the phage data.Plaque assays are more straightforward to analyse in this context, as there are no donors to worry about and 'recipients' are in excess.

REVIEWER COMMENTS
Reviewer #5 (Remarks to the Author): I was asked here to comment specifically on concerns about the methodology relating to conjugation rates, and remaining concerns of reviewers 3 and 4.
Response: Thank you very much for your time and for your oversight regarding the lengthy discussions involving our conjugation data and modelling conjugation rates/frequencies.Your valuable insights and comments have further improved the rigor of our findings, and we have addressed these concerns in our revised manuscript accordingly.We present below our point-by-point response: On the specific point of which formulas to use to calculate conjugation, I do agree with the authors.They have followed reviewers' requests to use Simonsen's endpoint model or its corrections.Prolonged culturing is not a problem as even the original Simonsen's endpoint model does not assume that the endpoint is still during the exponential phase; differences in growth rate are accounted for by the extended Simonsen's model described in Huisman et al and used here.
Response: Thank you for confirming that the conjugation methods we used were appropriate and that we have diligently followed the reviewer's advice throughout these iterations.Since the conjugation frequencies have now been measured by at least five different calculation methods, we have described the results from original SM method in the main text and described the other calculations in the supplementary data (Fig. S5-S9).All the necessary bacterial parameters for the calculation of conjugation frequency have been compiled into the supplementary datasets 1-4.These datasets contain all raw experimental data (donor, recipient, and transconjugant densities), as well as growth rates required for the Simonsen's method.
However, I do agree with the reviewers' worry about the data being inconclusive/unclear.
Firstly, I suspect this is partly due to the manuscript having gone through many revisions and reshuffling, it would need to be read again carefully with fresh eyes for global coherence (as an example, Fig 2 title only fits 2a and maybe b but not c to e).This also affects the conjugation rates results and methods: the method section does mix experimental methods (flow cytometry, plating, microscopy) and formulas for conjugation rate in a very confusing way.From the methods, plating data seem to still be analysed with T/N, flow cytometry by T/N and microscopy by T/D.The results shown in the main manuscript are sometimes summary data, sometimes detailed cytometry plots that I believe should all go in the supplementary data.
Response: The manuscript has gone through many iterations in direct response to the reviewer's suggestions; however, we unreservedly apologise if this has resulted in any confusion.To try providing further clarity on the key messages from our data, we have thoroughly revised both results (L184-222, L238-261) and method sections (L486-603).Further, we have undertaken the following: (i) Firstly, the title of Fig. (ii) Secondly, since the conjugation frequency have been repeated numerous times with at last five different calculation methods (T/N, T/R, T/D, SM and ASM), we should clearly state the differences in each conjugation method.The choice of flow cytometry, plating or microscopy offered three different ways for quantifying the bacterial densities of the donor, recipient and transconjugants.We subsequently calculated the transfer frequency by using different bacterial growth parameters (e.g., time, bacterial growth rate, initial/final population density) obtained by the above methods.Therefore, to improve clarity and scientific rigor, we have re-organised the method section in a more streamlined manner, (L489-549), and the method for conducting time-course conjugation experiment (linked to Fig. 3a-b) has been described in a separate paragraph (L583-L603).All related raw data and calculation file are available in supplemental datasets 1-4.
(iii) Thirdly, we have kept the results of transfer rates obtained from the original Simonsen's endpoint model (SM, the unit of transfer rate is mL• cell -1 •h -1 ) in the main figures (Fig. 2d-c and Fig. 3b-c), while the conjugation frequency calculated by the other methods (T/N, T/R, T/D or ASM) we have described in the revised supplementary data -Fig.S5-S8.This is in accordance with the comments from reviewers' 3 and 4.Moreover, the main conjugation results have been revised thoroughly (L184-222, L238-261), and the detailed cytometry plots have been removed from Fig. 3.
The results also vary depending on which experimental method is used, and this is not discussed.I personally would not have asked for this many different methods, but as they give very different results, this needs at least mentioned.Figs 2d and 2e differ by around 3 orders of magnitude for the same plasmid: What could explain this, if all methods reliably evaluate donors, recipients and transconjugants?The unit of measurement is also lacking, making it hard to evaluate these rates (or to guess which calculation has been used).
Response: Thank you for these observations and it is indeed interesting that different methods and calculations can produce variable data, and thus potentially affect any conclusions.It is anticipated that variations in bacterial density may arise when measured by two distinct methods.We have uploaded the raw data of all bacterial parameters (bacterial density, growth rates, OD values, etc.).The unit of measurement was added in the y axis (mL• cell -1 •h -1 ).
The main conjugation results have been revised thoroughly (L184-222, L238-265) to accommodate these differences.We appreciated the variations observed in plasmid transfer observed in different recipient-donor combinations, but it is also clear (Fig. 2d-e and supplementary Fig. S5-S6) that the majority of the seven TRMs strains, have showed higher conjugation permissiveness compared to the parental strain and therefore, our overall conclusions, caveats notwithstanding, have not deviated from our original submission.
There are also a few worrying facts in the plots: Response: We apologise for this oversight.The reason why 3x10 -16 appeared twice on the y axis is because we set the decimals as integers.We have now corrected this error in the revised Fig. 3c.When we applied the ASM calculation from Huisman's suggested online conjugator (doi:10.1016/j.plasmid.2022.1026272022), some replicates did not give a value (indicated as NA), and that is the reason for the missing replicates in Fig. S6 ASM -pA/C-MCR-8.
A very large amount of data is now presented, but not all of them are discussed, instead transfer rates are claimed to be constantly/consistently higher, which is not always true.E.g. line 222, MCR-8 is claimed to have "constantly higher transfer rates in the evolved d10-2 clone" -this is not true at 12h as shown in Fig 3b .And at 16h from Fig 3a there are no more transconjugants either -maybe the calculated transfer rate is higher but then providing the raw data might help understand why -does the effect arise from less donors or recipients?So any effect is not as consistent as the authors imply.
Response: Thank you for your valuable feedback.We have revised our results analysis to provide a more measured description of the transfer rates, taking into account specific time points and variations observed from the experimental data.The main conjugation results have also been thoroughly revised (L184-222, L238-261).Moreover, we also compared the differences across timepoints using two-way ANOVA(L247-249), and confirmed that the transfer rates of pFII_MCR-8 were significantly affected by both mating times and nsrR variant strains.And the increased transfer rates were observed in at least four timepoints in both d10-2 and ΔnsrR strains (L249-255).
Additionally, we have provided raw data to accommodate a better understanding of any observed effects and their underlying causes, such as variations in donor or recipient abundance (supplementary datasets 1-4).
P-values are shown for each time point / strain, but with so many conditions tested it is not clear if the global effect (evolved clones vs ancestor, or at least d10-2 clone across timepoints) is significant, and with which method.
Response: The statistical analysis was performed by Holm-Sidak corrected two sampled t-test and P-values denote the statistical difference between each evolved strain and the ancestor kp85anc.The p-values were displayed on the corresponding bars (Fig. 2 and Fig. 3).The significant variability of plasmid transfer rate among TRM strains and ancestor was analyzed by one-way ANOVA (L203-208, and P values was added in a new supplementary Table S6), with the majority of TRM strains showing higher conjugation rates compared to the parental strain.Moreover, we also compared the differences across timepoints using two-way ANOVA(L247-249), and confirmed that the transfer rates of pFII_MCR-8 were significantly affected by both mating times and nsrR variant strains.And the increased transfer rates were observed in at least four timepoints in both d10-2 and ΔnsrR strains (L249-255).
Finally, the raw data need to be available to the reader.What is presented now is only end estimates of the conjugation rate, but not the raw experimental data: donor, recipient and transconjugant densities (or proportions in the case of flow cytometry) need at least to be provided, plus the growth rates needed for Simonsen's method.
Response: Thank you for your feedback regarding the availability of raw data.All the necessary bacterial parameters for the calculation of conjugation frequencies are now compiled into supplementary datasets 1-4.These datasets contain all the raw experimental data, including donor, recipient, and transconjugant densities, as well as growth rates required for Simonsen's method.
Overall, I believe the conjugation data are worth publishing -and do certainly not need more experiments with more methods!-but the existing data need analysed in a more streamlined way to make the possible patterns clearer.
Response: Thank you for your assessment of our manuscript and confirming that no additional experiments are needed.We fully acknowledge your suggestion to analyse the existing data in a more streamlined and coherent manner, and highlight key differences more clearly.We have re-analysed our conjugation data and have attempted to described it in a clearer and more concise way in both the results (L184-223, L238-265) and method sections (L499-605).
Two added notes, even if it is further from what I was asked to comment on: i) the refs cited L261 seem to be about transformation, not conjugation.And ii) I believe that the general argument of this manuscript about evolution of permissiveness to MGEs via down regulation of defense systems could be also supported by insisting more on the phage data.Plaque assays are more straightforward to analyse in this context, as there are no donors to worry about and 'recipients' are in excess.
Response: Thank you for your additional notes.As rightly observed, these two references describe natural plasmid transformation; however, the basic parameters of plasmid transfer can still apply.Additionally, we acknowledge your suggestion regarding the phage data and the potential to further support the manuscript's message regarding the evolution of mobile genetic element permissiveness.We have utilised several plaque assays to strengthen our findings (Fig. 4 and Fig. S10-S12) and also further emphasized the phage findings in the discussion (L364-372, 391-395).
have been reversed.the clarification of no change to the other antibiotics tested was also added in L127-128.5. Fig 2b: gene names seem to be written in to different polices + it would be useful to highlight genes involved in Ab resistance (those represented in fig 2c).

Fig. 3
Fig.3 Increased conjugation rates of AMR plasmids were constantly observed in evolved and ΔnsrR knockout clones across 24 hours.(measured by flow cytometry, the full figure legend was provided in the main text) Fig.2c-d(new data, revised in the main Fig.2c-d) showing the transfer of four AMR plasmid in seven evolved strains and Kp85anc strain, based on Simonsen's end-point method.The different plasmid types were distinct with different colors, and the bacterial density were also measured by two methods, flow cytometry and selective agar plating.
Fig.S1 (new data) comparing the growth rates between evolved strains and ancestral Kp85anc strain.
conjugation rates instead of conjugation frequencies.Conjugation rates correct for the potential biases introduced by the difference in growth rates of donors, recipients and transconjugants.There are different methods to calculate conjugation rates, such as the end point method described by Simonsen et al. (DOI: 10.1099/00221287-136-11-2319) or other more modern methods described in Huisman et al. (DOI: 10.1016/j.plasmid.2022.102627).
2 has been revised (L884): "The genetic mutations and downregulation of bacterial defense systems leading to enhanced conjugation rate of AMR plasmids."We have also revised the figure legends for Fig.2and Fig.3as requested.
Fig 3c pX3-NDM y scale has 3. 10-16 repeated twice; and some bars have 1 single replicate visible and yet an associated p-value (Fig S6).